Agent skill

Sergei Mikhailov Tg Channel Reader

by aAAaqwq in aAAaqwq/AGI-Super-Team

Read posts and comments from Telegram channels via MTProto (Pyrogram or Telethon).

MITAuto-check passed

Install Sergei Mikhailov Tg Channel Reader

skills CLI
$ npx skills add aAAaqwq/AGI-Super-Team --skill sergei-mikhailov-tg-channel-reader -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aAAaqwq/AGI-Super-Team sergei-mikhailov-tg-channel-reader --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/tg-channel-reader .claude/skills/sergei-mikhailov-tg-channel-reader && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
sergei-mikhailov-tg-channel-reader
GitHub stars
105
Used in
1 other repo
Token cost
~4.6k tokens
SKILL.md length
1,599 words
Files
18
Skills in repo
167
Repo updated
First seen
Licence
MIT

At a glance

Read posts and comments from Telegram channels via MTProto (Pyrogram or Telethon).

  • Works in 5 steps: Get API Credentials → Save Credentials → Install & Configure → …
  • SKILL.md covers Exec Approvals, When to Use, Quick Start and Commands, plus 4 more sections
  • Runs Python and Shell scripts from its folder; calls pip, bash and python3; reaches t.me

What it does

Sergei Mikhailov Tg Channel Reader is an agent skill from aAAaqwq/AGI-Super-Team. Read posts and comments from Telegram channels via MTProto (Pyrogram or Telethon). Fetch recent messages and discussion replies from public or private channels by time window.

Its SKILL.md is about 4.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 17 other files (for example `CHANGELOG.md`, `CLAUDE.md` and `DISCLAIMER.md`).

It works with Telegram. The repository describes itself as: An installable, cross-framework AI organization: C-suite agents, expert subagents, curated skills, independent review, and one-command setup across 18 AI client/runtime adapters. The licence is MIT.

Example prompts

  • “/sergei-mikhailov-tg-channel-reader”

Requirements

  • Python 3
  • A Bash shell
  • Docker

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Get API Credentials
  2. Save Credentials
  3. Install & Configure
  4. Authenticate
  5. Verify

What it can do on your machine

Read from SKILL.md and the folder at commit 7cefd81. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Python and Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • pip
    • bash
    • python3
    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • t.me

    Also links to:

    • docs.openclaw.ai

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Sergei Mikhailov Tg Channel Reader loads about 4.6k tokens when it runs. Until then it costs about 53 tokens; SKILL.md has 1,599 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~53
When it runs · the whole SKILL.md, loaded when a task matches
~4.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from aAAaqwq/AGI-Super-Team at commit 7cefd81, republished under its MIT licence (© aAAaqwq). 1,599 words, ~4,637 tokens.

Download SKILL.mdSave it as .claude/skills/sergei-mikhailov-tg-channel-reader/SKILL.md (or your agent's skills folder). This skill also uses 17 other files; get the full folder from GitHub.
name
sergei-mikhailov-tg-channel-reader
description
Read posts and comments from Telegram channels via MTProto (Pyrogram or Telethon). Fetch recent messages and discussion replies from public or private channels by time window.

tg-channel-reader

Read posts and comments from Telegram channels using MTProto (Pyrogram or Telethon). Works with any public channel and private channels the user is subscribed to. Supports fetching discussion replies (comments) for individual posts.

Security notice: This skill requires TG_API_ID and TG_API_HASH from my.telegram.org. The session file grants full Telegram account access — store it securely and never share it.


Exec Approvals

Just installed via clawhub install? Complete Setup & Installation (below) first — the skill needs pip install, credentials, and a session file before exec approvals matter.

OpenClaw blocks unknown CLI commands by default. The user must approve tg-reader commands before they can run. If the command hangs or the user says nothing is happening — exec approval is likely pending.

Run from the skill directory — checks prerequisites, installs pip packages if needed, and prints the approval commands to run:

bash
cd ~/.openclaw/workspace/skills/sergei-mikhailov-tg-channel-reader
bash setup-tg-reader.sh
Manual CLI approval
bash
openclaw approvals allowlist add --gateway "$(which tg-reader)"
openclaw approvals allowlist add --gateway "$(which tg-reader-check)"
openclaw approvals allowlist add --gateway "$(which tg-reader-telethon)"
Alternative: approve on first use
  1. Control UI — open http://localhost:18789/, find the pending approval for tg-reader, click "Always allow". Docs
  2. Messenger (Telegram, Slack, Discord) — the bot sends an approval request with an <id>. Reply: /approve <id> allow-always. Other options: allow-once, deny.

The approval prompt appears in the Control UI or as a bot message — not in the agent's conversation. This is a common source of confusion.


When to Use

  • User asks to "check", "read", or "monitor" a Telegram channel
  • Wants a digest or summary of recent posts
  • Asks "what's new in @channel" or "summarize last 24h from @channel"
  • Wants to track or compare multiple channels
  • Wants channel info (title, description, subscribers) — use tg-reader info

Quick Start

bash
# 1. Run pre-flight diagnostic (fast, no Telegram connection)
tg-reader-check

# 2. Get channel info
tg-reader info @channel_name

# 3. Fetch recent posts
tg-reader fetch @channel_name --since 24h

tg-reader: command not found? Run bash setup-tg-reader.sh from the skill directory (it will install the package), or manually: cd ~/.openclaw/workspace/skills/sergei-mikhailov-tg-channel-reader && pip install .


Commands

tg-reader-check — Pre-flight Diagnostic

Always run before fetching. Fast offline check — no Telegram connection needed.

bash
tg-reader-check
tg-reader-check --config-file /path/to/config.json
tg-reader-check --session-file /path/to/session

Returns JSON with "status": "ok" or "status": "error" plus a problems array.

Verifies:

  • Credentials available (env vars or ~/.tg-reader.json)
  • Session file exists on disk (with size, modification date)
  • At least one MTProto backend installed (Pyrogram or Telethon)
  • Detects stale sessions (config points to older file while a newer one exists)
tg-reader info — Channel Info
bash
tg-reader info @channel_name

Returns title, description, subscriber count, and link.

tg-reader fetch — Read Posts
bash
# Last 24 hours (default)
tg-reader fetch @channel_name --since 24h

# Last 7 days, up to 200 posts
tg-reader fetch @channel_name --since 7d --limit 200

# Multiple channels (fetched sequentially with 10s delay between each)
tg-reader fetch @channel1 @channel2 @channel3 --since 24h

# Custom delay between channels (seconds)
tg-reader fetch @channel1 @channel2 @channel3 --since 24h --delay 5

# Fetch posts with comments (single channel only, limit auto-drops to 30)
tg-reader fetch @channel_name --since 7d --comments

# More comments per post, custom delay between posts
tg-reader fetch @channel_name --since 24h --comments --comment-limit 20 --comment-delay 5

# Skip posts without text (media-only, no caption)
tg-reader fetch @channel_name --since 24h --text-only

# Human-readable output
tg-reader fetch @channel_name --since 24h --format text

# Write output to file instead of stdout (saves tokens)
tg-reader fetch @channel_name --since 24h --output
tg-reader fetch @channel_name --since 24h --comments --output comments.json

# Use Telethon instead of Pyrogram (one-time)
tg-reader fetch @channel_name --since 24h --telethon

# Read unread mode — only fetch new (unread) posts, no --since needed
# Requires "read_unread": true in ~/.tg-reader.json
tg-reader fetch @channel_name

# Override read_unread mode (fetch everything, don't update state)
tg-reader fetch @channel_name --since 7d --all

# Custom state file location
tg-reader fetch @channel_name --since 24h --state-file /path/to/state.json
tg-reader auth — First-time Authentication
bash
tg-reader auth

Creates a session file. Only needed once.


Read Unread Mode

Only return new (unread) posts — the skill remembers what you've already seen. Useful for daily digests and monitoring workflows.

Setup

Option A — config file (~/.tg-reader.json):

json
{
  "api_id": 12345,
  "api_hash": "...",
  "read_unread": true
}

Option B — env var (works with ~/.openclaw/openclaw.json):

bash
export TG_READ_UNREAD=true

Env vars take priority over the config file. This lets you enable read_unread via openclaw.json Docker env alongside TG_API_ID/TG_API_HASH.

State is stored in ~/.tg-reader-state.json (configurable via "state_file" in config, TG_STATE_FILE env var, or --state-file flag).

Behavior
  • --since is not needed when read_unread is enabled — the skill automatically returns all unread posts regardless of time
  • First run (no prior state for channel): --since applies as usual (default 24h); state file created
  • Subsequent runs: only posts newer than the last read are returned; --since is ignored
  • --all flag: bypasses read_unread mode — fetches everything by --since without updating state (preserves your position)
  • New channel: behaves like a first run (no prior state)
  • No new posts: state unchanged, count: 0 returned
Examples
bash
# With read_unread enabled — just fetch, no --since needed
tg-reader fetch @channel_name

# First run for a new channel — --since determines initial window
tg-reader fetch @new_channel --since 7d

# Override: fetch everything, don't update tracking state
tg-reader fetch @channel_name --since 7d --all
Output

When read_unread mode is active, the JSON output includes a read_unread field:

json
{
  "channel": "@channel_name",
  "read_unread": {"enabled": true},
  "count": 5,
  "messages": [...]
}

With --all: "read_unread": {"enabled": true, "overridden": true}

Limitations
  • Tracking is post-level only — new comments on already-read posts are not caught
  • If a channel changes its username, tracking resets (state is keyed by username)
  • Concurrent runs for the same channel are safe but last writer wins
Diagnostic

tg-reader-check reports tracking status:

json
{
  "tracking": {
    "read_unread": true,
    "state_file": "~/.tg-reader-state.json",
    "state_file_exists": true,
    "tracked_channels": 3
  }
}

Output Format

info
json
{
  "id": -1001234567890,
  "title": "Channel Name",
  "username": "channel_name",
  "description": "About this channel...",
  "members_count": 42000,
  "link": "https://t.me/channel_name"
}
fetch
json
{
  "channel": "@channel_name",
  "fetched_at": "2026-02-22T10:00:00Z",
  "since": "2026-02-21T10:00:00Z",
  "count": 12,
  "messages": [
    {
      "id": 1234,
      "date": "2026-02-22T09:30:00Z",
      "text": "Post content...",
      "views": 5200,
      "forwards": 34,
      "link": "https://t.me/channel_name/1234",
      "has_media": true,
      "media_type": "MessageMediaType.PHOTO"
    }
  ]
}
fetch with --comments
json
{
  "channel": "@channel_name",
  "fetched_at": "2026-02-28T10:00:00Z",
  "since": "2026-02-27T10:00:00Z",
  "count": 5,
  "comments_enabled": true,
  "comments_available": true,
  "messages": [
    {
      "id": 1234,
      "text": "Post content...",
      "has_media": false,
      "comment_count": 2,
      "comments": [
        {
          "id": 5678,
          "date": "2026-02-28T09:35:00Z",
          "text": "Great post!",
          "from_user": "username123"
        }
      ]
    }
  ]
}

Notes:

  • comments_available: false — channel has no linked discussion group (no comments possible)
  • comments_error on a message — rate limit hit for that post's comments
  • from_user may be null for anonymous comments
  • Images/videos in comments are not analyzed — only text is captured
  • Default post limit drops to 30 when --comments is active (override with --limit)

After Fetching

  1. Parse the JSON output
  2. Posts with images/videos have has_media: true and a media_type field. Their text is in the text field (from the caption). Do not skip posts just because they have media — they often contain important text.
  3. Images and videos are not analyzed (no OCR/vision) — only the text/caption is returned.
  4. Summarize key themes, top posts by views, notable links
  5. If comments_enabled: true, analyze comment sentiment and key themes alongside the main posts
  6. Save summary to memory/YYYY-MM-DD.md if user wants to track over time
Saving to File (Token Economy)

Use --output when the result is large (especially with --comments) and you don't need to analyze it immediately. The full data goes to a file, and stdout returns only a short confirmation — this saves tokens.

Periodic updates pattern: set up a cron task that runs tg-reader fetch @channel --comments --output comments.json on schedule. The file gets updated regularly. When the user asks to analyze comments — read the file instead of re-fetching. This avoids consuming tokens on every fetch.

When --output is used without a filename, the default is tg-output.json. Stdout confirmation:

json
{"status": "ok", "output_file": "/absolute/path/to/tg-output.json", "count": 12}
Saving Channel List

Store tracked channels in TOOLS.md:

markdown
## Telegram Channels
- @channel1 — why tracked
- @channel2 — why tracked

Error Handling

Errors include an error_type and action field to help agents decide what to do automatically.

Channel Errors
error_typeMeaningaction
access_deniedChannel is private, you were kicked, or access is restrictedremove_from_list_or_rejoin — ask user if they still have access; if not, remove the channel
bannedYou are banned from this channelremove_from_list — remove the channel, tell the user
not_foundChannel doesn't exist or username is wrongcheck_username — verify the @username with the user
invite_expiredInvite link is expired or invalidrequest_new_invite — ask user for a new invite link
flood_waitTelegram rate limitwait_Ns — waits ≤ 60 s are retried automatically; longer waits return this error
comments_multi_channel--comments used with multiple channelsremove_extra_channels_or_drop_comments — use one channel at a time
Show full SKILL.md (635 more words)Show less
System Errors
ErrorAction
Session file not foundRun tg-reader-check — use the suggestion from output
Missing credentialsGuide user through Setup (Step 1-2 below)
tg-reader: command not foundRun bash setup-tg-reader.sh from the skill directory, or manually: pip install . Fallback: python3 -m tg_reader_unified
AUTH_KEY_UNREGISTEREDSession expired — delete and re-auth (see below)
Session Expired
bash
rm -f ~/.tg-reader-session.session
tg-reader auth
Auth Code Not Arriving

Use the verbose debug script for full MTProto-level logs:

bash
python3 debug_auth.py

Warning: debug_auth.py deletes existing session files before re-authenticating. It will ask for confirmation first.


Library Selection

Two MTProto backends are supported:

BackendCommandNotes
Pyrogram (default)tg-reader or tg-reader-pyrogramModern, actively maintained
Telethontg-reader-telethonAlternative if Pyrogram has issues

Switch persistently: export TG_USE_TELETHON=true Switch one-time: tg-reader fetch @channel --since 24h --telethon


Setup & Installation

Full details in README.md.

Step 1 — Get API Credentials

Go to https://my.telegram.org → API Development Tools → create an app → copy api_id and api_hash.

Step 2 — Save Credentials

Recommended (works in agents and servers):

bash
cat > ~/.tg-reader.json << 'EOF'
{
  "api_id": YOUR_ID,
  "api_hash": "YOUR_HASH"
}
EOF
chmod 600 ~/.tg-reader.json

Alternative (interactive shell only):

bash
export TG_API_ID=YOUR_ID
export TG_API_HASH="YOUR_HASH"

Set these in your current shell session. Avoid writing TG_API_HASH to shell profiles (~/.bashrc) — use ~/.tg-reader.json instead for persistent storage.

Note: Agents and servers don't load shell profiles. Use ~/.tg-reader.json (the recommended method above) for non-interactive environments.

Step 3 — Install & Configure
bash
npx clawhub@latest install sergei-mikhailov-tg-channel-reader
cd ~/.openclaw/workspace/skills/sergei-mikhailov-tg-channel-reader
bash setup-tg-reader.sh

The setup script: installs Python packages (pip install .), checks credentials and session, runs tg-reader-check, and prints the exec approval commands for you to run manually.

On Linux with managed Python (Ubuntu/Debian), use a venv before running the setup script:

bash
python3 -m venv ~/.venv/tg-reader
echo 'export PATH="$HOME/.venv/tg-reader/bin:$PATH"' >> ~/.bashrc && source ~/.bashrc
<details>
<summary>Manual install (without setup script)</summary>
bash
cd ~/.openclaw/workspace/skills/sergei-mikhailov-tg-channel-reader
pip install pyrogram tgcrypto telethon && pip install .
openclaw approvals allowlist add --gateway "$(which tg-reader)"
openclaw approvals allowlist add --gateway "$(which tg-reader-check)"
</details>
Step 4 — Authenticate
bash
tg-reader auth

Pyrogram will ask to confirm the phone number — answer y. The code arrives in the Telegram app (not SMS).

Step 5 — Verify
bash
tg-reader-check

Should return "status": "ok". If not — fix the reported issues and re-run bash setup-tg-reader.sh.


Scheduled Tasks & Cron

This skill needs network access (MTProto connection to Telegram servers) and a session file. How you configure OpenClaw cron depends on the session target.

Important: When setting up a scheduled task that uses tg-reader, tell the user which approach you're using and what it means — so they can make an informed choice.

The cron task sends a reminder to the main agent session. The agent then runs tg-reader in the main environment where the skill, credentials, and session file are already available.

Pros: No extra configuration — everything works out of the box. Cons: Not fully autonomous — the task sends a system event, the agent picks it up and executes. Requires payload.kind: "systemEvent" (OpenClaw cron API limitation for main target).

How to set up:

  1. Create a cron task with sessionTarget: "main" and payload.kind: "systemEvent"
  2. In the task description, include the exact tg-reader command to run
  3. The agent receives the reminder and executes the command in its main session
Option B — sessionTarget: "isolated" (autonomous, complex setup)

The cron task runs in a Docker container — fully autonomous, no agent interaction needed. However, the container starts empty: no skill, no credentials, no session file.

Pros: Fully autonomous — runs on schedule without agent involvement. Cons: Requires Docker setup; session file must be mounted into the container (may not work reliably — session files are tied to the machine and Telegram may invalidate them in a new environment).

Required configuration in ~/.openclaw/openclaw.json:

json
{
  "agents": {
    "defaults": {
      "sandbox": {
        "docker": {
          "setupCommand": "clawhub install sergei-mikhailov-tg-channel-reader && cd ~/.openclaw/workspace/skills/sergei-mikhailov-tg-channel-reader && pip install pyrogram tgcrypto telethon && pip install .",
          "env": {
            "TG_API_ID": "YOUR_ID",
            "TG_API_HASH": "YOUR_HASH",
            "TG_READ_UNREAD": "true"
          }
        }
      }
    }
  }
}

Session file caveat: The Telegram session file (~/.tg-reader-session.session) must also be available inside the container. This may require Docker volume mounting and might not work reliably — Telegram can invalidate sessions when they appear from a different environment. If you encounter AUTH_KEY_UNREGISTERED errors in isolated mode, switch to Option A.

Explicit paths (both options)

When ~/ is not available or points to a different location, use explicit paths:

bash
tg-reader-check \
  --config-file /home/user/.tg-reader.json \
  --session-file /home/user/.tg-reader-session

tg-reader fetch @channel --since 6h \
  --config-file /home/user/.tg-reader.json \
  --session-file /home/user/.tg-reader-session

Both flags work with all subcommands and both backends.


Security

  • Session file (~/.tg-reader-session.session) grants full account access — keep it safe
  • Never share or commit TG_API_HASH or session files
  • TG_API_HASH is a secret — store in env vars or config file, never in git

© aAAaqwq, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 17 other files in skills/tg-channel-reader of aAAaqwq/AGI-Super-Team.

  • SKILL.md
  • .gitignore
  • CHANGELOG.md
  • CLAUDE.md
  • DISCLAIMER.md
  • LICENSE
  • README.md
  • README_TELETHON.md
  • TESTING_GUIDE.md
  • debug_auth.py
  • reader.py
  • reader_telethon.py
  • setup-tg-reader.sh
  • setup.py
  • test_session.py
  • tg_check.py
  • tg_reader_unified.py
  • tg_state.py

Open the folder on GitHubat commit 7cefd81

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in aAAaqwq/AGI-Super-Team, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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    aAAaqwq/AGI-Super-Team

    Publish and manage content on 知识星球 (zsxq.com). An agent skill from aAAaqwq/AGI-Super-Team.

    105 GitHub stars~1.5k tokensUpdated 2 days ago
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Works with

Questions about Sergei Mikhailov Tg Channel Reader

What does Sergei Mikhailov Tg Channel Reader do?

Read posts and comments from Telegram channels via MTProto (Pyrogram or Telethon). Sergei Mikhailov Tg Channel Reader is an agent skill from aAAaqwq/AGI-Super-Team. Read posts and comments from Telegram channels via MTProto (Pyrogram or Telethon).

How do I install Sergei Mikhailov Tg Channel Reader in Claude Code?

Run `npx skills add aAAaqwq/AGI-Super-Team --skill sergei-mikhailov-tg-channel-reader -a claude-code`. Or copy the skill folder (skills/tg-channel-reader in aAAaqwq/AGI-Super-Team) into .claude/skills/sergei-mikhailov-tg-channel-reader in your project. Claude Code loads it when a task matches its description.

How do I install Sergei Mikhailov Tg Channel Reader in Codex?

Run `npx skills add aAAaqwq/AGI-Super-Team --skill sergei-mikhailov-tg-channel-reader -a codex`. Or copy the skill folder (skills/tg-channel-reader in aAAaqwq/AGI-Super-Team) into .agents/skills/sergei-mikhailov-tg-channel-reader in your project. Codex loads it when a task matches its description.

Can I use Sergei Mikhailov Tg Channel Reader in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aAAaqwq/AGI-Super-Team --skill sergei-mikhailov-tg-channel-reader -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sergei-mikhailov-tg-channel-reader, .gemini/skills/sergei-mikhailov-tg-channel-reader, .github/skills/sergei-mikhailov-tg-channel-reader and .opencode/skills/sergei-mikhailov-tg-channel-reader in your project.

What does Sergei Mikhailov Tg Channel Reader need to run?

Going by SKILL.md and its folder, Sergei Mikhailov Tg Channel Reader needs Python and a shell for the scripts in its folder and the command-line tools its instructions call (pip, bash, python3 and npx). Our summary lists: Python 3; A Bash shell; Docker.

Does Sergei Mikhailov Tg Channel Reader access the network?

SKILL.md names 2 domains. In commands or code: t.me; the agent is likely to contact it when it follows the instructions. As links in the text: docs.openclaw.ai. This is read from the text; nothing was executed.

Is Sergei Mikhailov Tg Channel Reader safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Sergei Mikhailov Tg Channel Reader use?

Sergei Mikhailov Tg Channel Reader is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Sergei Mikhailov Tg Channel Reader use?

About 4.6k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Sergei Mikhailov Tg Channel Reader?

Skills that share tags, products or a category with Sergei Mikhailov Tg Channel Reader: Dependency Watch (telegramdesktop/tdesktop, 33k stars), Perform Task (telegramdesktop/tdesktop, 33k stars), Custom Mode Creator for claude-mem (thedotmack/claude-mem, 99k stars) and Continue (telegramdesktop/tdesktop, 33k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Sergei Mikhailov Tg Channel Reader?

aAAaqwq (a GitHub user) maintains it in aAAaqwq/AGI-Super-Team, which has 105 GitHub stars. The repository holds 167 skills in this directory. The repository was last updated on October 8, 2026.

Source: aAAaqwq/AGI-Super-Team on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.